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Control and Perception Framework for Deep Sea Mining Exploration

Carlotta Sartore, Ricard Campos, Josep Quintana, Enrico Simetti, Rafael García, Giuseppe Casalino

Year
2019
Citations
14

Abstract

This paper presents the control and perception framework used in the ROBUST EU Horizon 2020 project, aimed at integrate different technologies for developing an underwater autonomous robotic system for exploring deep-sea mining sites. The vehicle firstly collects data of the initial zone of interest and it selects a sub area which is the most probable to contain a manganese nodule field; then it carries out a low altitude survey. When a possible nodule is detected by the cameras, the vehicle lands on the seafloor, allowing the following fixed based manipulation which is designed to perform the nodule analysis. The work reports the implemented control and perception architecture and the preliminary pool experiments results.

Keywords

PerceptionComputer scienceArchitectureRemotely operated underwater vehicleDeep learningField (mathematics)Work (physics)Artificial intelligenceControl (management)Robot

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